1. Field of the Disclosure
The application generally relates to data compression, and more particularly to decompression of data compressed using adaptive discrete cosine transform process.
2. Description of the Related Art
Compression is a key factor of multimedia. An effective digital compression can reduce the cost as well as increase the quality of video displayed over any digital communication channel. One application for compression techniques is the motion picture industry.
For several decades, the motion picture industry has depended on the duplication, distribution, and projection of celluloid film for delivering programming material to geographically diverse theaters around the country and the world. To a large extent, the methods and mechanisms for the distribution of film material have remained relatively unchanged for decades. Generally, the current film duplication and distribution process involves generating a master film copy from an exceptional quality camera negative, producing a distribution negative from the master film copy, and producing distribution prints from the distribution negative. Depending on the size of the release or number of copies desired for distributing the film, there may be more intermediate steps or multiple copies produced at each stage. The distribution prints (known as “positives”) are then distributed by physical means to various theaters and displayed using a film projector.
Although the distribution process above works, there are inherent limitations. Due to the use of celluloid material for the film and the bandwidth limitations of the film media, there are restrictions on the ability to provide high fidelity multi-channel audio programming. Then, there is the high expense of making a large number of film duplicates, which can cost several hundreds of dollars for each copy of each feature length film. There is also the expense, complexity, and delay associated with physically distributing large canisters of celluloid film to a large and growing number of theater locations.
Accordingly, new and emerging technologies are being developed to provide alternative approaches to the ongoing film distribution problems. One such method is the use of satellite transmission. However, in order to transmit a high quality audio/video (AV) signal in “real-time,” the data rate requirement (in bits per second) is on the order of 1.5 billion bits per second. This high data rate requires the capacity equivalent of an entire satellite to transmit even a single program, which is prohibitively expensive. Therefore, satellite transmissions are not yet commercially viable for the distribution of high quality AV material.
Advances in digital technology have also led to a distribution concept whereby programming material is electronically stored in a digitized format. The digitized images may be distributed on various magnetic media or compact optical discs, or transmitted over wired, fiber optic, wireless, or satellite communication systems. These storage mediums typically have storage capacities ranging from about 4.5 gigabytes (GB) to about 18 GB. However, an average two hour movie having an average image compressed bit rate of about 40 Mbps for the image track and about eight Mbps for audio and control information, requires approximately 45 GB of storage space. Thus, even if a high storage capacity DVD-ROM disk is implemented, a two-hour movie requires use of multiple DVD-ROM disks for adequate capacity.
To reduce the data rate requirement for the storage of high quality electronic images, compression algorithms are being developed. One digital dynamic image compression technique capable of offering significant compression while preserving the quality of image signals utilizes adaptively sized blocks and sub-blocks of encoded discrete cosine transform (DCT) coefficient data. This technique will hereinafter be referred to as the adaptive block size discrete cosine transform (ABSDCT) method. The adaptive block sizes are chosen to exploit redundancy that exists for information within a frame of image data. The technique is disclosed in U.S. Pat. No. 5,021,891, entitled “Adaptive Block Size Image Compression Method And System,” assigned to the assignee of the present application and incorporated herein by reference. DCT techniques are also disclosed in U.S. Pat. No. 5,107,345, entitled “Adaptive Block Size Image Compression Method And System,” assigned to the assignee of the present application and incorporated herein by reference. Further, the use of the ABSDCT technique in combination with a Discrete Quadtree Transform technique is discussed in U.S. Pat. No. 5,452,104, entitled “Adaptive Block Size Image Compression Method And System,” also assigned to the assignee of the present application and incorporated by reference herein. The systems disclosed in these patents utilize intraframe encoding, wherein each frame of an image sequence is encoded without regard to the content of any other frame.
Generally, compression of data streams comprises quantization after discrete cosine transform. Moreover, different quantization parameters are often used for different data block sizes. Similarly, decompression of compressed data streams comprises inverse quantization and different quantization parameters are used for different data block sizes.
In a typical discrete cosine transform, the size of each data block is fixed and the same quantization parameter may be used for quantization and inverse quantization of each data block. However, if ABSDCT is implemented, data blocks may be divided into different combinations of sub-blocks for the discrete cosine transform. Accordingly, depending on how a data block is divided, different quantization parameters are used for quantization of each data block. Similarly, depending on how a data block is divided, different quantization parameters are used for inverse quantization of each data block. Therefore, in order to perform inverse quantization during decompression, the appropriate quantization parameters need to be known for each data block being processed.